RADCOM announced today NetTalk – Generative AI (GenAI) applications that are part of its RADCOM ACE portfolio, enabling operators to adopt the power of Generative AI and trusted data to manage their network operations faster and cost-effectively. By enhancing engineering team productivity, optimizing 5G network quality, and simultaneously driving down costs, these innovative applications contribute to an improved customer experience.
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Operators can talk with their network and leverage rich insights through GenAI and custom large language models (LLM). Executives and engineers can use natural language to tap into the wealth of data RADCOM ACE produces as it actively monitors the network. They can easily understand the impact of issues on network services and how they affect the customer experience. Leveraging the cloud-native architecture of RADCOM ACE, NetTalk applications can be built on public cloud platforms such as Microsoft Azure, AWS, and Google Cloud. This makes it easy to build and scale GenAI-powered applications.
“Data-driven decision-making is one of a telecom operator’s top priorities as it can make a difference in preventing customer-affecting degradations. With our cloud-based service assurance platform and trustable data, RADCOM is among the first service assurance vendors to bring the power of GenAI to address this challenge of rapidly gaining insights from the data collected from the network,” said Eyal Harari, CEO of RADCOM. “This new offering will help our customers simplify their assurance workflows, enhancing their ability to maintain high-quality 5G services proactively.”
RADCOM NetTalk leverages RADCOM’s unique core-to-RAN, correlated, and trustable datasets and RADCOM’s cloud-native open platform to offer advanced, customizable solutions for operators worldwide. These GenAI applications will help operators manage 5G complexity and data overload to ensure 5G service quality and gain real-time information about what is happening in their network.
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RADCOM NetTalk applications comprise the following:
- Orchestrating a series of reason-dependent actions, simplifying insights drawn from network trace data. For example, a user may prompt the application to point to geographies, times, and why video services didn’t meet certain quality thresholds.
- Using natural language models to visualize deep insights from processed data in response to free-style user prompts. The results of such an analysis can be displayed in proprietary analytics tools or using leading industry tools on cloud platforms like Microsoft Azure, Amazon Web Services (AWS), and Google Cloud.
- An AI agent that is a network expert equipped with an embedded GenAI reasoning engine, assists users in configuring the network and products according to industry standards and utilizing data from automated assurance.
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